ライフサイエンスコーパス: decisional

1 r is entirely decision dependent (i.e., post-decisional).

2 urgency) and delay components (pre- and post-decisional).

3 responses are neither entirely pre- nor post-decisional.

4 , the tool underwent validated assessment of decisional acceptability, decisional conflict, and decis

5 to, adaptation, and consequences of the post-decisional accumulation process.

6 keholders, a QPL was created to address core decisional and informational needs of surgical patients.

7 We discuss these results in light of decisional and postdecisional accounts of confidence and

8 e, we report three new lines of evidence for decisional and postdecisional mechanisms arguing for the

9 es that social media sites serve for patient decisional and support needs.

10 al decision support can better standardize a decisional approach and also allow a unique degree of pe

11 d the sensory, motor, or sensorimotor (i.e., decisional) aspects of the task.

12 In contrast, decisional authority is a nondelegable parental right an

13 effort to provide patients with appropriate decisional authority over their own medical choices, sha

14 h while limiting patients' end of life (EOL) decisional authority through advance directives or surro

15 e first distinguish decisional priority from decisional authority.

16 roles: no role, witness, surrogate, and full decisional authority.

17 ocity, prevent prejudice, donor safety net), decisional autonomy (body ownership, right to know, vali

18 67), we find that advisers who give advisees decisional autonomy rather than offering paternalistic a

19 tients and advisees in general react to full decisional autonomy when making difficult decisions unde

20 medical decision making that prioritize full decisional autonomy.

21 included review of goals, tailored feedback, decisional balance exercise, role plays, and referrals.

22 The decisional biases were consistent with a criterion chang

23 To decouple sensory from decisional biases, here we asked humans to perform a sim

24 icipants, 30 exhibited sensory biases and 15 decisional biases.

25 r associated with activation of language and decisional brain areas during false recognitions of low-

26 ination) was generally the best predictor of decisional capacity (particularly in the understanding c

27 The need to evaluate decisional capacity among patients in treatment settings

28 irical investigations have directly compared decisional capacity among patients with a serious mental

29 e research is needed on methods of enhancing decisional capacity among those with impaired competence

30 considered limiting life-support who lacked decisional capacity and a legally recognized surrogate d

31 so, as requirements for formal assessment of decisional capacity are becoming more common, there is a

32 ymptoms shown to be associated with impaired decisional capacity are not unique to schizophrenia and

33 to identify those needing more comprehensive decisional capacity assessment and/or remediation effort

34 earch participants who warrant more thorough decisional capacity assessment and/or remediation effort

35 The authors identified 23 decisional capacity assessment instruments and evaluated

36 t perform as well as the controls on initial decisional capacity assessment.

37 Decisional capacity differed among the 3 groups; there w

38 This study ascertains the decisional capacity for informed consent in schizophreni

39 ors critically reviewed existing measures of decisional capacity for research and treatment.

40 tical measures for screening and documenting decisional capacity in people participating in different

41 The potential impairment of decisional capacity in persons with schizophrenia is cen

42 ability, and correlates of treatment-related decisional capacity in this patient population.

43 Decisional capacity is generally conceptualized to inclu

44 Subjects who performed poorly on the decisional capacity measure received an educational inte

45 Decisional capacity was assessed for 30 research subject

46 underscore the importance of considering how decisional capacity will be assessed in all types of res

47 r hospitalized incarcerated patients lacking decisional capacity, admissions of these patients genera

48 t is built upon the elements of information, decisional capacity, and volunteerism.

49 y lower scores on two of the four aspects of decisional capacity.

50 itive dysfunction, psychiatric symptoms, and decisional capacity.

51 lusions), were significantly associated with decisional capacity.

52 r hospitalized incarcerated persons who lack decisional capacity.

53 ct for their preferences regardless of their decisional capacity.

54 al (auditory and visual stimulus locations), decisional (causal inference), and motor response dimens

55 simple scenarios, is affected by sensory and decisional choice biases.

56 recalibration relies on distinct spatial and decisional codes that are expressed with opposite gradie

57 y processing hierarchy multiplex spatial and decisional codes to adapt flexibly to the changing senso

58 ticipants, with longitudinal improvements in decisional comfort and overall HRQOL over time and minim

59 Decisional comfort was high at baseline (median [IQR] DR

60 Secondary outcomes were use of SDM, decisional comfort, readiness to change, and preventive

61 ble options, accuracy of risk estimates, and decisional comfort.

62 y associated with the peak latency of the P3 decisional component.

63 Cataract-related knowledge and decisional confidence (decisional conflict scale (DCS))

64 A tendency towards slightly higher decisional confidence and lower regret was found in the

65 In both groups, decisional confidence was high and regret after surgery

66 Patients showed a high decisional confidence with a study group mean DCS score

67 treatment (the primary outcome), as well as decisional conflict (a secondary outcome), were measured

68 's depression and stress predicted their own decisional conflict (actor effects), as well as their pa

69 .35 to 2.09; P<0.001), and reduced patients' decisional conflict (adjusted mean difference -6.3 (95%

70 Importantly, SDM was associated with less decisional conflict (B=-0.66, R(2)=0.567, P<0.01) and de

71 ession symptoms was not related to their own decisional conflict (beta=0.07; P=0.37).

72 ive symptoms were related to greater patient decisional conflict (beta=0.16; P<0.05), whereas caregiv

73 <0.001) was significantly related to greater decisional conflict (both actor effects).

74 (d, -0.01; lower bound 97.5% CI, -0.06), and decisional conflict (d, -0.12; upper bound 97.5% CI, 2.0

75 Patients who experience less decisional conflict (DC) are more engaged in treatment a

76 Primary outcome was preoperative decisional conflict (Decisional Conflict Scale); seconda

77 interval, 3.20-14.78), and experienced less decisional conflict (mean difference = -5.04; 95% confid

78 self-efficacy (mean score 85.9/100) and low decisional conflict (mean score 20.9/100).

79 (actor effects), as well as their partner's decisional conflict (partner effects).

80 more likely to know their risk, and had less decisional conflict along with greater involvement in SD

81 management, there was a slight reduction in decisional conflict and an improvement in HbA1c levels w

82 SDM is associated with lower decisional conflict and decisional regret; and no differ

83 for decision making, as well as with greater decisional conflict and distress, even after adjustment

84 rgoing coronary angiogram procedures reduces decisional conflict and improves value congruence and th

85 also suggested that decision aids decreased decisional conflict and increased satisfaction with the

86 hypothesized that the co-primary outcomes of decisional conflict and informed choice regarding immuno

87 Decisional conflict and patient demographic data were as

88 e were no partner effects identified between decisional conflict and perceived stress or depressive s

89 families of patients deemed at high risk for decisional conflict and provided feedback to the clinica

90 ledge about testing, risk comprehension, and decisional conflict and regret at 24 to 36 weeks' gestat

91 and actual outcomes resulting in significant decisional conflict and regret.

92 Preoperative decisional conflict did not differ between the groups (3

93 s more effective than usual care in reducing decisional conflict for choice of immunosuppressive medi

94 Secondary outcomes included decisional conflict immediately after intervention and 3

95 ived stress significantly predicting greater decisional conflict in both patients and caregivers.

96 at the COVID-19 pandemic was associated with decisional conflict in patients undergoing otolaryngolog

97 cision aid (DA) on the medical knowledge and decisional conflict in patients with early-stage PTC con

98 eparation for decision making, distress, and decisional conflict in separate models, controlling for

99 ompared with attention control, no effect on decisional conflict occurred at 1 month.

100 Significant differences did not emerge in decisional conflict or regret.

101 Decisional Conflict Scale (DCS) score, which was scored

102 related knowledge and decisional confidence (decisional conflict scale (DCS)) were assessed as well a

103 e counselor group had lower mean scores on a decisional conflict scale (P =.04) and, in low-risk wome

104 tervention group had a significantly reduced decisional conflict scale compared with control (unadjus

105 ention patients felt better informed (median Decisional Conflict Scale informed subscore: 8 versus 17

106 Mean total decisional conflict scale score significantly improved f

107 utcome was preoperative decisional conflict (Decisional Conflict Scale); secondary outcomes included

108 assessments of decisional conflict using the Decisional Conflict Scale, depressive symptoms using the

109 Prevalence of DC (qualitative, Decisional Conflict Scale, SURE questionnaire) and DR (q

110 l conflict, was assessed using the validated decisional conflict scale.

111 tient satisfaction was measured by using the decisional conflict scale.

112 Mean decisional conflict score at 1 month did not differ betw

113 16.9%] vs 55.6% [22.6%]; P < .001) and lower decisional conflict scores (mean [SD], 12.7 [16.6] vs 18

114 High decisional conflict scores improved after both the decis

115 in the 5 decision quality measures (eg, mean decisional conflict scores were 17.2 and 17.5, respectiv

116 rvention surrogates had greater reduction in decisional conflict than control surrogates (mean differ

117 ent-caregiver dyads completed assessments of decisional conflict using the Decisional Conflict Scale,

118 vation, support and resources; (2) patients' decisional conflict varied substantially, driven by uncl

119 nted without bias for a "best choice." Lower decisional conflict was associated with caregiver-report

120 Unresolved decisional conflict was lower in the decision aid versus

121 Decisional conflict was measured using the low-literacy

122 Decisional conflict was more prevalent among non-White t

123 lidation, the group with the highest rate of decisional conflict was non-White patients with no colle

124 Across both models, decisional conflict was significantly correlated within

125 RAI treatment was significantly greater and decisional conflict was significantly reduced in the DA

126 Patient anxiety and decisional conflict were significantly lower after RS re

127 ion aids improve patient knowledge and lower decisional conflict without raising anxiety levels, they

128 l and statistically significant reduction in decisional conflict, 21.8 (standard error [SE], 2.5) ver

129 history and current exercise, SDM (SDM-Q-9), decisional conflict, and decisional regret.

130 ated assessment of decisional acceptability, decisional conflict, and decisional self-efficacy.

131 ration to make a decision for testing, lower decisional conflict, and greater decisional self-efficac

132 ic groups as measured by knowledge transfer, decisional conflict, and patient involvement in SDM.

133 atus) on the outcomes of knowledge transfer, decisional conflict, and patient involvement in SDM.

134 n making, information comprehension, values, decisional conflict, and preferred treatment.

135 ids (DAs) increase patient knowledge, reduce decisional conflict, and promote shared decision making

136 ences of surrogates (psychological distress, decisional conflict, and quality of communication) and p

137 mic medications, patient-reported medication decisional conflict, and satisfaction with antihyperglyc

138 Primary outcomes were patient knowledge and decisional conflict, and the secondary outcome was an ob

139 Patients completed measures for decisional conflict, anxiety, and quality of life.

140 ddition, we documented effects on knowledge, decisional conflict, anxiety, quality of life, patient i

141 id, patient decision aid, or both) had lower decisional conflict, better shared decision making, and

142 There were no differences between groups in decisional conflict, decision process quality, shared de

143 Secondary outcomes included decisional conflict, difficulty making the decision, can

144 s consistently report low levels of anxiety, decisional conflict, harm, or regret.

145 BREASTChoice did not improve decisional conflict, match between preferences and treat

146 e impact of PCI Choice on patient knowledge, decisional conflict, participation in decision-making, a

147 surrogate decision makers and often lead to decisional conflict, psychological distress, and treatme

148 A survey assessed knowledge, preferences, decisional conflict, shared decision-making, preferred t

149 Exploratory outcomes included decisional conflict, values concordance, trust, the pres

150 The primary outcome, decisional conflict, was assessed using the validated de

151 or the effect of the patient decision aid on decisional conflict, which did not reach statistical sig

152 o promote automatic responding and to reduce decisional conflict.

153 lues-based decisions, while clearly reducing decisional conflict.

154 criteria identified 873 patients at risk for decisional conflict.

155 surgery may be fraught with uncertainty and decisional conflict.

156 ariables, with higher scores indicating more decisional conflict.

157 s about COVID-19, most screened positive for decisional conflict.

158 artner effects were identified in predicting decisional conflict.

159 s in patients also predicted greater patient decisional conflict.

160 atrial fibrillation and its management, and decisional conflict.

161 ng did not yield a significant difference in decisional conflict.

162 sthetic heart valve selection does not lower decisional conflict.

163 eported using a tailored approach to resolve decisional conflicts about life support and attempted to

164 eported using a tailored approach to resolve decisional conflicts about life support and attempted to

165 Here, we isolated postdecisional from decisional contributions to metacognition by analyzing n

166 proach treatment decisions with a desire for decisional control, which may increase after their consu

167 in noise (internal or external), a change in decisional criteria, or signal enhancement.

168 he effects of expectation can also be due to decisional criterion shifts independent of any sensory c

169 confidence estimates and by the influence of decisional cues on confidence estimates.

170 herapy, whenever possible, to address common decisional dilemmas.

171 : control preference roles reflect levels of decisional engagement; clinicians control information fl

172 n terms of the computational process of post-decisional evidence accumulation.

173 t we have poor metacognition for unconscious decisional evidence.

174 th conscious and unconscious accumulation of decisional evidence.

175 perceptual processing or to post-perceptual decisional factors.

176 Consistent with this, a decisional flowchart for predicting fibrosis was suggest

177 rtainties for future research, and propose a decisional framework for clinicians to support prescript

178 and healthcare workers allows for real-time decisional guidance; however, its impact on neonatal hea

179 Persons with decisional impairment due to Alzheimer's disease are as

180 uthors examined the effects of cognitive and decisional impairment on willingness to participate in r

181 mer's disease group, the presence of greater decisional impairment tended to predict less willingness

182 ssion errors) on a Go/NoGo task and measured decisional impulsivity (delay discounting) using the Mon

183 r the efficacy of atomoxetine in remediating decisional impulsivity in CUD.

184 Atomoxetine selectively reduced decisional impulsivity in patients with CUD by reducing

185 Here we assess decisional impulsivity in subjects with obsessive compul

186 cated in inhibitory function but its role in decisional impulsivity is less well-understood.

187 ting impulsivity: R1 was not associated with decisional impulsivity on the MCQ or inhibitory control

188 nucleus is causally implicated in increasing decisional impulsivity with less accumulation of evidenc

189 impairments are observed across subtypes of decisional impulsivity, possibly reflecting uncertainty

190 le for the value-coding medial SN network in decisional impulsivity, while the salience-coding ventra

191 eparable components: value, probability, and decisional impulsivity.

192 or associative-limbic subthalamic nucleus in decisional impulsivity.

193 evidence and delay discounting are forms of decisional impulsivity.

194 last resort" due to their vulnerability and decisional incapacity.

195 ase, as well as integration and weighting of decisional information, which is coupled to alpha phase

196 , there was a small difference in adolescent decisional involvement and vaccine-related confidence an

197 A probabilistic decisional model simulated a cohort of 1000 NAFLD patien

198 pharmacotherapy decision-making: (1) patient decisional needs included lack of awareness of a choice

199 ight the importance of addressing modifiable decisional needs of patients through enhanced shared dec

200 Nested qualitative data assessing OIT decisional needs were supplemented with evidence-synthes

201 Patients with HFrEF have several decisional needs, which are consistent with those that m

202 ess patients' preoperative informational and decisional needs.

203 C) was created to help identify preoperative decisional needs.

204 Post-decisional neural signals have been identified that are

205 Decisional outcomes, cardiovascular risk factor outcomes

206 risk factors and health behaviors as well as decisional outcomes.

207 nd content of the system could be adapted to decisional participants' unique characteristics, abiliti

208 phasizing patient accountability, restricted decisional power, protecting unit interests), and entren

209 We first distinguish decisional priority from decisional authority.

210 clinician is in a better position to assume decisional priority when a child probably can be cured.

211 s (and children, when appropriate) to assume decisional priority when there are two or more clinicall

212 why clinicians sometimes justifiably assume decisional priority when there is one best medical choic

213 This distinction enables us to analyze decisional priority without diminishing parental authori

214 irst identifies a preferred choice exercises decisional priority.

215 ty responses could represent a higher-level, decisional process of cognitive monitoring, though that

216 FG and IFG to implement a "winner takes all" decisional process.

217 The results show that decisional processes are rapidly implemented during move

218 ed that temporal expectations speeded up non-decisional processes but had no effect on decision forma

219 e LC in regulating the behavioral outcome of decisional processes contrasts with more traditional vie

220 The contribution of sensory and decisional processes to perceptual decision making is st

221 ether they are early sensory effects or late decisional processes.

222 We examined online decisional processing in humans by asking them to make r

223 al modelling to identify alterations in post-decisional processing that contribute to the phenomenon

224 ision aids can improve patient knowledge and decisional quality but are infrequently used in real-wor

225 Other measures of decisional quality were not improved, and engagement of

226 t knowledge but did not significantly impact decisional quality.

227 risk = 1.7 [95% CI, 1.2 to 2.5]) and family decisional regret (144 participants; difference in means

228 ratio, 0.23; 95% CI, 0.06-0.86) and parental decisional regret (adjusted odds ratio, 0.42; 95% CI, 0.

229 ians was generally associated with decreased decisional regret (all ORs with 95% CIs greater than 1.1

230 l conflict (B=-0.66, R(2)=0.567, P<0.01) and decisional regret (B=-0.37, R(2)=0.180, P<0.001) and no

231 ssessed as well as one-month postoperatively decisional regret (decision regret scale (DRS)) and will

232 th 55.3% (n=99) reporting moderate to severe decisional regret (DRS [decisional regret scale]>=25).

233 -0.003; 95% CI, -0.03 to 0.03; P = .83) and decisional regret (effect size, 1.32; 95% CI, -3.77 to 6

234 mewhat useful and 50.3% (88/161) reported no decisional regret (median 0, mean 10, range 0-100).

235 = 0.30; 95% CI, 0.02-0.54; P = .05), greater decisional regret (r = -0.54; 95% CI, -0.67 to -0.38; P

236 ed survey instruments indicated low rates of decisional regret and high levels of satisfaction with d

237 ey were donor conceived reported the highest decisional regret and represented the largest proportion

238 Decisional regret and satisfaction with decision to unde

239 ent, patient-centered decisions with reduced decisional regret and work-related stress experienced by

240 with low satisfaction with decision or high decisional regret due to the lack of variation in these

241 he validated SDMQ9, and (4) an assessment of decisional regret in relation to SDM components and the

242 ons between home time and QoL, function, and decisional regret in the survey data were analyzed using

243 e compromise outcomes and impose unnecessary decisional regret on clinicians and patients alike.

244 incorporated into the last decision, and (4) decisional regret related to their last treatment decisi

245 d SDMQ9 scale for shared decision-making and Decisional Regret Scale (DRS) was distributed using the

246 ure was heightened regret as measured by the Decisional Regret Scale.

247 g moderate to severe decisional regret (DRS [decisional regret scale]>=25).

248 Prevalence of decisional regret was also high with 55.3% (n=99) report

249 Decisional regret was inversely associated with home tim

250 Decisional regret was low and did not differ across grou

251 scale, with higher scores indicating higher decisional regret) and significantly increased over time

252 and 3 months after intervention, knowledge, decisional regret, and anxiety immediately after interve

253 literacy, contextual factors (acculturation, decisional regret, and satisfaction with informed consen

254 xual functioning and distress, cancer worry, decisional regret, and surgical outcomes.

255 more engaged in treatment and less prone to decisional regret, nervousness, and fretting.

256 mbers assessed their psychological symptoms, decisional regret, patient functional outcome, and patie

257 ise, SDM (SDM-Q-9), decisional conflict, and decisional regret.

258 ological Consequences Questionnaire, and (4) decisional regret.

259 nces for SDM and the association of SDM with decisional regret.

260 ch as JAK inhibitors may be related to lower decisional regret.

261 on, 3-Level questionnaire; and local therapy decisional regret.

262 pletion of testing, anxiety, depression, and decisional regret.

263 ts (N = 54) met our definition of heightened decisional regret.

264 ssociated with lower decisional conflict and decisional regret; and no difference in postdiagnosis ex

265 nsibility-relatives explain how they endorse decisional responsibility but do not experience it as a

266 on the patient, family members feel a strong decisional responsibility that is not experienced as a b

267 nd psychosocial characteristics on patients' decisional role was also examined.

268 e between patients' and physicians' views on decisional role.

269 h greater self-efficacy desiring more active decisional roles (P = .08).

270 g to interpret clinical information, and (4) decisional roles and relationships with clinicians.

271 Decisional satisfaction was lowest among minority women

272 ess to information about reconstruction, and decisional satisfaction.

273 icipants using the heuristic showed combined decisional (selection) and skill (execution) advantages,

274 ecision-aid, noting good acceptability, high decisional self-efficacy (mean score 85.9/100) and low d

275 ting, lower decisional conflict, and greater decisional self-efficacy.

276 onal acceptability, decisional conflict, and decisional self-efficacy.

277 y affect the decision process itself, or non-decisional (sensory/motor) processes.

278 ional biases, which make them susceptible to decisional shortcuts, or heuristics.

279 elies on supramodal confidence estimates and decisional signals that are shared across sensory modali

280 ex continual results in distinctive types of decisional situations.

281 hoice behaviour, including motor inhibition, decisional slowing, and value sensitivity.

282 central death regulator, is required at the decisional stage of apoptosis.

283 then how severely to react are two distinct decisional stages underpinned by different neurocognitiv

284 Primary clinicians followed PPC decisional strategies (eg, use patients' health prioriti

285 C identified a need for more information and decisional support during preoperative conversations tha

286 Findings highlight the need for targeted decisional support for PLWD as well as caregivers who fa

287 and feedback to clinical staff, computerized decisional support systems, and specialist-level pain co

288 y: emotional support; communication support; decisional support; and, if indicated, anticipatory grie

289 Impairments appear to be more specific to decisional than motor impulsivity, which might reflect d

290 M organization based on automated alerts and decisional trees enabled a focus on clinically relevant

291 For this purpose, we recommend the use of decisional trees, being the parameters under study those

292 y nurses and cardiologists; and (2) selected decisional trees.

293 ity patterns in frontoparietal cortices code decisional uncertainty consistent with these spatial tra

294 ed or when competing stimuli are similar and decisional uncertainty is high.

295 For patients with decisional uncertainty or a desire to maintain the statu

296 Because of high decisional uncertainty, additional information regarding

297 standing of randomization, and exhibited low decisional uncertainty.

298 iarity, and prognostic uncertainty), seeking decisional validation (a familial obligation, alleviatin

299 ed, the mechanisms by which attention alters decisional weighting of sensory evidence (choice-bias co

300 tivity (sensory processing) and choice bias (decisional weighting) for attended information.